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sidenav header background[5月21日] 计量金融与大数据分析workshop
发布日期:2021-05-18 09:09 来源:
题目:基于高维预测变量和变量筛选方法的原油期货波动率的预测研究(Volatility Forecasts of Crude Oil Futures with Variable Selection Approaches and High-dimension Predictors)
时间:2021年5月21日(周五)10:00 AM -- 11:30 AM
地点:经济学院107会议室(线下)
主持人:(国发院)沈艳、黄卓、孙振庭、张俊妮
(新结构)胡博
(经院)王一鸣、王熙、刘蕴霆
主讲人:罗嘉雯(华南理工大学工商管理学院副教授)
报告摘要:
We augment the HAR model with additional information channels to forecast realized volatility of WTI futures prices. These channels include stock markets, sentiment indices, commodity and FX markets, and text-based Google indices. We then apply four differing predictor selection techniques to identify the most suitable endo- and exogenous factors which improve baseline model forecasts. We show that machine learning generated forecasts provide better forecasting quality and that portfolios which are constructed with these forecasts outperform their competing models. We find LASSO and SSVS to provide outperforming forecasts and portfolio weights. Analyzing the selection process, we show that variable choices vary across forecasting horizon. Variable selection produces clusters and provides evidence that there are structural changes with regard to the significance of information channels.
主讲人简介:
罗嘉雯,现任华南理工大学工商管理学院副教授。中山大学本科、博士,澳大利亚昆士兰大学联合培养博士。她的主要研究领域是金融经济学、金融高频时间序列和金融风险管理等。她在国内外知名金融经济期刊发表多篇高水平论文,这些期刊包括International Journal of Forecasting, European Journal of Finance, Journal of Futures Markets, Energy Economics和管理科学学报等。曾获国家自然科学基金青年基金项目、教育部人文社会科学基金、广东省自然科学基金面上项目等国家省部级项目资助。